Getting Around “Undruggable” Proto-Oncogenes

While multiple human cancers are associated with oncogene amplification,

epigenetic targets causing amplification such as transcription factors were once considered “undruggable,” or

unlikely to be modulated with a small molecule drug.

Generally, these proteins lack surface involutions suitable for high-affinity binding by small molecules. But by thinking outside the “loop” or the usual structures required for drug targets, investigators have been making headway in targeting the formerly untargetable.

Multiple human cancers are associated with c-Myc gene amplification including lung carcinoma breast carcinoma, colon carcinoma, and neuroblastoma. The protogene also plays a key role in cell cycle regulation, metabolism, apoptosis, differentiation, cell adhesion, as well as in tumorigenesis, and participates in regulating hematopoietic homeostasis. Its gene product functions as a transcription regulator, part of

an extensive network of interacting factors regulating the expression, it has been estimated, of more than 15 percent of all human genes.

While Myc oncogene family members, for example, act as key drivers in human cancers,

they have been considered undruggable as

they encode transcription factors and carry out essential functions in proliferative tissues,

suggesting that their inhibition could cause severe side effects.

And from a chemist’s point of view, these proteins’ surfaces are not amenable to binding drugs. In an online dialog posted on the NCI’s website in October of 2010, an investigator noted, “We don’t know how to interfere with these factors or their activities in clinical settings because, in general,

we lack the means to inhibit proteins that are not enzymes.”

But by preventing key protein-protein interactions that enable the actions of these transcriptional drivers, scientists are drugging the formerly undruggable.

To Drug the Undruggable Target

One such approach published in Nature in 2009 by a team of Harvard scientists who was reported that they had successfully targeted a “master” protein, Notch1, which had been considered “untouchable” by conventional drugs. The protein is a

like other transcription factors has proven an elusive drug target due to its structure.

The scientists said they had designed

a synthetic, cell-permeable alpha-helical peptide, SAHM1,

which could target a critical protein-protein interface in the notch transactivation complex.

The drug molecule enters cells and interferes with a protein-protein interaction essential for the transmission of cell growth signals via the Notch pathway.

The researchers tested the drug using cells from patients with T-cell acute lymphoblastic leukemia (T-ALL) and a mouse model of the disease. The Notch1 gene is mutated in half of patients with T-ALLand

produces an inappropriately active Notch1 protein.

Activated Notch signaling has been seen in several other cancers including lung, ovarian, and pancreatic cancer, and melanoma.

“We’ve drugged a so-called undruggable target,” said Gregory L. Verdine, Ph.D., Erving professor of chemistry at Harvard University. “This study validates the notion that you can target a transcription factor

by choosing a new class of molecules, namely stapled peptides.”

He added that, because the molecular logic of these proteins is similar to Notch1’s,

this strategy might work for other transcription factors as well.

Targeting BET

Another emerging approach to drugging the undruggable is to target the bromo and extra C-terminal domain (BET) family of bromodomains that are

involved in binding epigenetic “marks” on histone proteins.

Four members of this 47-protein family interact with chromatin including histone acetylasesand nucleosome remodeling complexes. Bromodomain proteins act as chromatin “readers” to recruit chromatin-regulating enzymes, including

“writers” and “erasers” of histone modification, to target promoters and to regulate gene expression.

As mentioned in a previous GEN article, epigenetic control systems generally involve three types of proteins:

While investigators have considered that the precise function of the so-called BET bromodomain remains incompletely defined,

proteins containing this domain have become another epigenetic target for drug development companies.

these domains may allow researchers a way to get at oncogenic targets that were once thought undruggable including the proto-oncogene Myc.

Small molecule inhibition of BET protein bromodomains also selectively suppresses other genes such as Bcl-2 that have important roles in cancer, as well as some NF-κB-dependent genes that have roles in both cancer and inflammation. Small molecule inhibition of BET bromodomains

leads to selective killing of tumor cells across a range of hematologic malignancies and in subsets of solid tumors.

BRD4 also contributes to regulation of both cell cycle and transcription of oncogenes, HIV, and human papilloma virus (HPV). Despite its role in a broad range of biological processes, the precise molecular mechanism of BRD4function, until very recently, remained unknown.

In 2010, investigators reported in Nature that they had identified a cell-permeable small molecule that bound competitively to bromodomains, or acetyl-lysine recognition motifs. Competitive binding by the small molecule JQ1, the investigators reported,

The authors say that these data established proof-of-concept for targeting protein–protein interactions of epigenetic readers, and could provide a versatile

chemical scaffold for the development of chemical probes more broadly throughout the bromodomain family.

More recently, writing in the Journal of Medicinal Chemistry, investigators at GlaxoSmithKline reported that they had successfully optimized

a class of benzodiazepines as BET bromodomain inhibitors, apparently without any prior knowledge of identified molecular targets.

Significant medicinal chemistry provided the bromodomain inhibitor, I-BET762 or GSK525762, which is currently in a Phase I clinical trial for the treatment of NUT midline carcinoma, a rare but lethal form of cancer, and other cancers.

Casting a Wide Net

Constellation Pharmaceuticals of Cambridge, MA, announced that it has initiated a Phase I clinical trial of CPI-0610,a novel small molecule BET protein bromodomain inhibitor, in patients with previously treated and progressive lymphomas. This first-in-human trial is currently open at Sarah Cannon Research Institute in Nashville, Tennessee, and at the John Theurer Cancer Center in Hackensack, New Jersey. Additional study sites in the U.S. will join the trial over the next several months. Studies of CPI-0610 are also planned in patients with multiple myeloma and in patients with acute leukemia or myelodysplastic syndrome.

Constellation’s CMO, Michael Cooper, M.D. told GEN that “small molecule inhibitors of BET protein bromodomains have demonstrated broad activity against hematologic malignancies in preclinical models. And this activity can be achieved in vivo with levels of compound exposure that are well tolerated. While we are encouraged by these observations, what really makes the area interesting is

the novel mechanism by which BET protein bromodomain inhibitors elicit their biologic effects.

They disrupt the interaction of BET proteins with acetylated lysine residues on histones and thereby

suppress the transcription of key cancer-related genes such as MYC, BCL-2, and a subset of NF-κB-dependent genes.

These genes have in the past been difficult to target with small molecules. In light of the breadth of the activity in preclinical models of hematologic malignancies and the important genes that are targeted, we intend to cast a wide net across hematologic malignancies in the clinic.”

Robert Sims, Ph.D., and senior director of biology at Constellation explained that BET protein bromodomain inhibition is only of several areas of interest for the company. “The BET proteins constitute one class of epigenetic targets, namely

molecules that recognize patterns in chromatin architecture and

either enhance or suppress gene transcription.

Constellation’s approach to epigenetics also includes programs in the enzymes that modify the architecture of chromatin, for example by the

methylation or demethylation of histone proteins (writers and erasers, respectively).

Even though our first drug candidate is directed against a set of reader proteins, we are also looking at inhibitors of the writer protein, EZH2, which is mutated in some types of non-Hodgkin lymphoma and overexpressed in many malignancies.”

In January 2012, Constellation and Genentech announced collaboration based on the science of epigenetics and chromatin biology to discover and develop innovative treatments for cancer and other diseases. Each company will each commit a significant portion of their research and development efforts to the advancement of programs under the collaboration, and each party will have the right to retain exclusive rights to programs emerging from the collaboration.

And more biotech giants can be expected to enter the field of epigenetics as smaller companies advance into the clinic with this novel approach to controlling gene expression gone wrong in cancer cells.

Employing Metabolomics in Cell Culture and Bioprocessing: Gaining greater predictability, control and quality

Challenges in developing and producing biotherapeutics are numerous and dynamic, including various market drivers and industry responses. Finding effective measures to support a foundation of control, predictability, and quality have been a concern and have paved the way to seeking out and applying newer technologies such as metabolomics successfully to bioprocessing. This webinar will first navigate through the landscape and challenges in developing and producing biotherapeutics. The journey continues with a walk through of the rationale for why metabolomics is a key tool for addressing critical bioprocessing needs followed by specific case studies and examples of how a functional metabolomic approach has been applied.

There are many relevant applications for functional metabolomics in bioprocessing starting with process development that include being able to: boost titer or productivity, improve product quality, enhance viability, or optimize defined media. The technology has be employed in biomarker discovery applications for the following purposes: to identify predictors of lactate consumption, to assess product quality, to predict indicative biomarkers of bioreactor performance or identify ideal clones. Lastly, functional metabolomics has been applied to enrich DOE experiments and troubleshooting for: historical deviation, process transfer, scale-up issues, disposable concerns, and lot or performance changes.

In part one I covered the basics of role of redox chemistry in immune reactions, the phagosome cauldron, and how bacteria bacteria, virus and parasites trigger the complex pathway of NO production and its downstream effects. While we move further in this post, the previous post can be accessed here.

In addition to eradicating pathogens, NO/RNS and ROS and their chemical interactions act as effective immunomodulators that regulate many cellular metabolic pathways and tissue repair and proinflammatory pathways. Figure 3 shows these pathways.

Regulation of iNOS enzyme activity is critical to NO production. Factors such as the availability of arginine, BH4, NADPH, and superoxide affect iNOS activity and thus NO production. In the absence of arginine and BH4 iNOS becomes a O2_/H2O2 generator (Vásquez-Vivar et al., 1999). Hence metabolic pathways that control arginine and BH4 play a role in determining the NO/superoxide balance. Arginine levels in cells depend on various factors such as type of uptake mechanisms that determine its spatial presence in various compartments and enzymatic systems. As shown in Fig3 Arginine is the sole substrate for iNOS and arginase. Arginase is another key enzyme in immunemodulation. AG is also regulated by NOS and NOX activities. NOHA, a product of NOS, inhibits AG, and O2–increases AG activity. Importantly, high AG activity is associated with elevated ROS and low NO fluxes. NO antagonises NOX2 assembly that in turn leads to reduction in O2_ production. NO also inhibits COX2 activity thus reducing ROS production. Thus, as NO levels decline, oxidative mechanisms increase. Oxidative and nitrosative stress can also decrease intracellular GSH (reduced form) levels, resulting in a reduced antioxidant capability of the cell.

Immune-associated redox pathways regulate other important metabolic cell functions that have the potential for widespread impact on cells, organs, and organisms. These pathways, such as mediated via methionine and polyamines, are critical for DNA stabilization, cell proliferation, and membrane channel activity, all of which are also involved in immune-mediated repair processes.

NO levels dictate the immune signaling pathway

NO/RNS and ROS actively control innate and adaptive immune signaling by participating in induction, maintenance, and/or termination of proinflammatory and anti-inflammatory signaling. As in pathogen eradication, the temporal and spatial concentration profiles of NO are key factors in determining immune-mediated processes.

Brune and coworkers (Messmer et al., 1994) first demonstrated that p53 expression was associated with the concentrations of NO that led to apoptosis in macrophages. Subsequent studies linked NO concentration profiles with expression of other key signaling proteins such as HIF-1α and Akt-P (Ridnour et al., 2008; Thomas et al., 2008). Various levels of NO concentrations trigger different pathways and expectedly this concentration-dependent profile varies with distance from the NO source.NO is highly diffucible and this characteristic can result in 1000 fold reduction in concentration within one cell length distance travelled from the source of production. Time course studies have also shown alteration in effects of same levels of NO over time e.g. NO-mediated ERK-P levels initially increased rapidly on exposure to NO donors and then decreased with continued NO exposure (Thomas et al., 2004), however HIF-1α levels remained high as long as NO levels were elevated. Thus some of the important factors that play critical role in NO effects are: distance from source, NO concentrations, duration of exposure, bioavailability of NO, and production/absence of other redox molecules.

Figure and legend credits: (Wink et al., 2011)

Fig 4: The effect of steady-state flux of NO on signal transduction mechanisms.

This diagram represents the level of sustained NO that is required to activate specific pathways in tumor cells. Similar effects have been seen on endothelial cells. These data were generated by treating tumor or endothelial cells with the NO donor DETANO (NOC-18) for 24 h and then measuring the appropriate outcome measures (for example, p53 activation). Various concentrations of DETANO that correspond to cellular levels of NO are: 40–60 μM DETANO = 50 nM NO; 80–120 μM DETANO = 100 nM NO; 500 μM DETANO = 400 nM NO; and 1 mM DETANO = 1 μM NO. The diagram represents the effect of diffusion of NO with distance from the point source (an activated murine macrophage producing iNOS) in vitro (Petri dish) generating 1 μM NO or more. Thus, reactants or cells located at a specific distance from the point source (i.e., iNOS, represented by star) would be exposed to a level of NO that governs a specific subset of physiological or pathophysiological reactions. The x-axis represents the different zone of NO-mediated events that is experienced at a specific distance from a source iNOS producing >1 μM. Note: Akt activation is regulated by NO at two different sites and by two different concentration levels of NO.

Species-specific NO production

The relationship of NO and immunoregulation has been established on the basis of studies on tumor cell lines or rodent macrophages, which are readily available sources of NO. However in humans the levels of protein expression for NOS enzymes and the immune induction required for such levels of expression are quite different than in rodents (Weinberg, 1998). This difference is most likely due to the human iNOS promotor rather than the activity of iNOS itself. There is a significant mismatch between the promoters of humans and rodents and that is likely to account for the notable differences in the regulation of gene induction between them. The combined data on rodent versus human NO and O2– production strongly suggest that in general, ROS production is a predominant feature of activated human macrophages, neutrophils, and monocytes, and the equivalent murine immune cells generate a combination of O2– and NO and in some cases, favor NO production. These differences may be crucial to understanding how immune responses are regulated in a species-specific manner. This is particularly useful, as pathogen challenges change constantly.

The next post in this series will cover the following topics:

The impact of NO signaling on an innate immune response—classical activation

NO and proinflammatory genes

NO and regulation of anti-inflammatory pathways

NO impact on adaptive immunity—immunosuppression and tissue-restoration response

An Investigation of the Potential of circulating Endothelial Progenitor Cells (cEPCs) as a Therapeutic Target for Pharmacological Therapy Design for Cardiovascular Risk Reduction: A New Multimarker Biomarker Discovery

Immunoreactivity of Nanoparticles

As nanotechnology progresses from research and development to commercialization and use, it is likely that manufactured nanomaterials and nanoproducts will be released into the environment.

Adverse effects of nanoparticles on human health depend on individual factors such as genetics and existing disease, as well as exposure, and nanoparticle chemistry, size, shape, agglomeration state, and electromagnetic properties. Animal and human studies show that inhaled nanoparticles are lessefficiently removed than larger particles by the macrophage clearance mechanisms in the lung,causing lung damage, and that nanoparticles can translocate through the circulatory, lymphatic, and nervous systems to many tissues and organs, including the brain.

The key to understanding the toxicity of nanoparticles is that their minute size, smaller than cells and cellular organelles, allows them to penetrate these basic biological structures, disrupting their normal function. Examples of toxic effects include tissue inflammation, and altered cellular redox balance toward oxidation, causing abnormal function or cell death. http://arxiv.org/ftp/arxiv/papers/0801/0801.3280.pdf

Some NPs happen to be toxic to biological systems, others are relatively benign, while others confer health benefits. As current knowledge of the toxicology of ‘bulk’ materials may not suffice in reliably predicting toxic forms of nanoparticles, ongoing and expanded study of ‘nanotoxicity’ will be necessary. For nanotechnologies with clearly associated health risks, intelligent design of materials and devices is needed to derive the benefits of these new technologies while limiting adverse health impacts.

Human skin, lungs, and the gastro-intestinal tract are in constant contact with the environment. While the skin is generally an effective barrier to foreign substances, the lungs and gastro-intestinal tract are more vulnerable. These three ways are the most likely points of entry for natural or anthropogenic nanoparticles. Injections and implants are other possible routes of exposure, primarily limited to engineered materials. Due to their small size, nanoparticles can translocate from these entry portals into the circulatory and lymphatic systems, and ultimately to body tissues and organs. Some nanoparticles, depending on their composition and size, can produce irreversible damage to cells by oxidative stress or/and organelle injury.

Are they biocompatible? Do the nanoparticles enter the lymphatic and circulatory systems? If not, do they accumulate in the skin and what are the long-term effects of accumulation? Do they produce inflammation? If they enter the lymphatic and circulatory system, is the amount significant? What are the long-term effects of this uptake? Related to the beneficial antioxidant properties of some nanomaterials, long-term effect need to be studied, in addition to the short-term antioxidant effect. What is the long-

term fate of these nanoparticles? Are they stored in the skin? Do they enter circulation? What happens when the nanoparticles undergo chemical reactions and lose their antioxidant properties?

For a full view of the questions needed to be addressed please visit. http://bdds.fudan.edu.cn/…/fdfa2aa9-df2b-4c9f-a2a5-a33ee29acb76.pdf

The answers to some of these questions are known, and will be presented in the chapter dedicated to nanoparticles toxicity, however most of the remaining questions still remain unanswered.

The immunostimulatory properties of nanoparticles discussed here include their antigenicity, adjuvant properties, inflammatory responses and the mechanisms through which nanoparticles are recognized by the immune system. Since this is a very complicated mechanism , the factors affecting the immune response are summaried here:

Size

Th1/Th2 stimulation

Adjuvent properties

Internalization/phagocytic uptake

Hapten properties

Particle clearance

Charge

Toxicity to immune cells

Binding plasma proteins

Particle clearance

Immune cell stimulation

Hydrophobicity

Interaction with plasma proteins

Internalization/phagocytic uptake

Immune cell stimulation

Particle clearance

Targeting

Immunogenicity

For example: In general, cationic (positively-charged) particles are more likely to induce inflammatory reactions than anionic (negativelycharged) and neutral species. For example, anionic generation- 4.5 PAMAM dendrimers did not cause human leukocytes (white blood cells) to secrete cytokines53 but cationic liposomes induced secretion of cytokines such as TNF, IL-12 and IFNγ. Systemic administration of another cationic nanoliposome alone or in combination with bacterial DNA did not induce cytokine production but increased the expression of DC surface markers, CD80/CD86, which are important in the inflammatory response.

Trace impurities within the nanomaterial formulation can also frequently induce an inflammatory response. Early studies suggest that carbon nanotubes induce inflammatory reactions, but a more recent study shows that they don’t when they are purified.

Another consideration in the inflammatory response is maintaining the Th1/Th2 response — the inflammatory reaction. triggered by Th cells that direct and activate other immune cells such as B and T cells and macrophages to secrete different cytokines. This response is important for protecting against cancer cells and pathogens and to avoid hypersensitivity (undesirable and exaggerated immune response) reactions. Several studies have addressed the influence of nanoparticles on Th1 and Th2 responses. Large (>1 μm) industrialized particles induced the Th1 response, whereas smaller ones (<500 nm) were associated with Th2.

Therefore, more structure–activity relationship studies are required to understand how size, surface modification and charge of engineered particles influence the Th1/Th2 balance

Particle stimulation of adaptive (acquired) immunity has also been described. For example, small (<100 nm) polystyrene particles promoted CD8 and CD4 T-cell responses and were associated with higher antibody levels than larger (>500 nm) particles. Understanding the mechanisms requires further investigation, and is important for nanovaccine formulation development.

Phagosome-mediated processing and presentation of nanoparticles may differ from that of ‘canonical’ antigens. Certain biodegradable nanoparticles can be taken up through conventional pathogen-specific routes and can stimulate inflammatory reactions just like pathogens

More mechanistic studies are required to understand how the immune system manages non-biodegradable components of nanoparticles (for example, metallic cores). Many questions remain regarding processing of multi-component and multi functional nanoparticles. Are the individual components (the coating, core, and so on) stable inside the phagosome or do they separate? Are the biodegradable and non-biodegradable components processed together or individually?

Immunotoxicological analysis of new molecular entities is not a straightforward process, and there is no universal guide for immunotoxicity.

Conclusions:

The mechanism of cellular uptake of nanoparticles and the biodistribution depend on the physico-chemical properties of the particles and in particular on their surface characteristics. Moreover, as particles are mainly recognized and engulfed by immune cells special attention should be paid to nano–immuno interactions. It is also important to use primary cells for testing of the biocompatibility of nanoparticles, as they are closer to the in vivo situation when compared to transformed cell lines.

Understanding the unique characteristics of engineered nanomaterials and their interactions with biological systems is key to the safe implementation of these materials in novel biomedical diagnostics and therapeutics.

The main challenge in immunological studies of nanomaterials is choosing an experimental approach that is free of falsepositive or false-negative readouts. The majority of the standard immunotoxicological methods are applicable to nanomaterials. However, as nanoparticles represent physically and chemically diverse materials, the classical methods cannot always be applied without modification, and novel approaches may be required. For example, many nanoparticles absorb in the UV–Vis range and some particles may catalyse enzyme reactions or quench fluorescent dyes commonly used as detection reagents in various end-point or kinetic assays. These and other methodological

challenges in preclinical evaluation of nanoparticles are reviewed in detail elsewhere.

Both ‘classical’ and novel imunotoxicological assessments of nanomaterials clearly need a scrupulous stepwise validation, standardization, and demonstration of their physiological relevance.

Industry, academics, and federal agencies are now collaborating to identify critical parameters in nanoparticles characterization and to establish acceptance criteria for nanomaterial-specific assays.

Nitric oxide (NO), reactive nitrogen species (RNS) and reactive oxygen species (ROS) perform dual roles as immunotoxins and immunomodulators. An incoming immune signal initiates NO and ROS production both for tackling the pathogens and modulating the downstream immune response via complex signaling pathways. The complexity of these interactions is a reflection of involvement of redox chemistry in biological setting (fig. 1)

Fig 1. Image credit: (Wink et al., 2011)

Previous studies have highlighted the role of NO in immunity. It was shown that macrophages released a substance that had antitumor and antipathogen activity and required arginine for its production (Hibbs et al., 1987, 1988). Hibbs and coworkers further strengthened the connection between immunity and NO by demonstrating that IL2 mediated immune activation increased NO levels in patients and promoted tumor eradication in mice (Hibbs et al., 1992; Yim et al., 1995).

In 1980s a number of authors showed the direct evidence that macrophages made nitrite, nitrates and nitrosamines. It was also shown that NO generated by macrophages could kill leukemia cells (Stuehr and Nathan, 1989). Collectively these studies along with others demonstrated the important role NO plays in immunity and lay the path for further research in understanding the role of redox molecules in immunity.

NO is produced by different forms of nitric oxide synthase (NOS) enzymes such as eNOS (endothelial), iNOS (inducible) and nNOS (neuronal). The constitutive forms of eNOS generally produce NO in short bursts and in calcium dependent manner. The inducible form produces NO for longer durations and is calcium independent. In immunity, iNOS plays a vital role. NO production by iNOS can occur over a wide range of concentrations from as little as nM to as much as µM. This wide range of NO concentrations provide iNOS with a unique flexibility to be functionally effective in various conditions and micro-environements and thus provide different temporal and concentration profiles of NO, that can be highly efficient in dealing with immune challenges.

Redox reactions in immune responses

NO/RNS and ROS are two categories of molecules that bring about immune regulation and ‘killing’ of pathogens. These molecules can perform independently or in combination with each other. NO reacts directly with transition metals in heme or cobalamine, with non-heme iron, or with reactive radicals (Wink and Mitchell, 1998). The last reactivity also imparts it a powerful antioxidant capability. NO can thus act directly as a powerful antioxidant and prevent injury initiated by ROS (Wink et al., 1999). On the other hand, NO does not react directly with thiols or other nucleophiles but requires activation with superoxide to generate RNS. The RNS species then cause nitrosative and oxidative stress (Wink and Mitchell, 1998).

The variety of functions achieved by NO can be understood if one looks at certain chemical concepts. NO and NO2 are lipophilic and thus can migrate through cells, thus widening potential target profiles. ONOO-, a RNS, reacts rapidly with CO2 that shortens its half life to <10 ms. The anionic form and short half life limits its mobility across membranes. When NO levels are higher than superoxide levels, the CO2-OONO–intermediate is converted to NO2 and N2O3 and changes the redox profile from an oxidative to a nitrosative microenvironment. The interaction of NO and ROS determines the bioavailability of NO and proximity of RNS generation to superoxide source, thus defining a reaction profile. The ROS also consumes NO to generate NO2 and N2O3 as well as nitrite in certain locations. The combination of these reactions in different micro-environments provides a vast repertoire of reaction profiles for NO/RNS and ROS entities.

The Phagosome ‘cauldron’

The phagosome provides an ‘isolated’ environment for the cell to carry out foreign body ‘destruction’. ROS, NO and RNS interact to bring about redox reactions. The concentration of NO in a phagosome can depend on the kind of NOS in the vicinity and its activity and other localised cellular factors. NO and is metabolites such as nitrites and nitrates along with ROS combine forces to kill pathogens in the acidic environment of the phagosome as depicted in the figure 2 below.

This diagram depicts the different nitrogen oxide and ROS chemistry that can occur within the phagosome to fight pathogens. The presence of NOX2 in the phagosomes serves two purposes: one is to focus the nitrite accumulation through scavenging mechanisms, and the second provides peroxide as a source of ROS or FA generation. The nitrite (NO2−) formed in the acidic environment provides nitrosative stress with NO/NO2/N2O3. The combined acidic nature and the ability to form multiple RNS and ROS within the acidic environment of the phagosome provide the immune response with multiple chemical options with which it can combat bacteria.

Bacteria

There are various ways in which NO combines forces with other molecules to bring about bacterial killing. Here are few examples

E.coli: It appears to be resistant to individual action of NO/RNS and H2O2 /ROS. However, when combined together, H2O2 plus NO mediate a dramatic, three-log increase in cytotoxicity, as opposed to 50% killing by NO alone or H2O2 alone. This indicates that these bacteria are highly susceptible to their synergistic action.

Staphylococcus: The combined presence of NO and peroxide in staphylococcal infections imparts protective effect. However, when these bacteria are first exposed to peroxide and then to NO there is increased toxicity. Hence a sequential exposure to superoxide/ROS and then NO is a potent tool in eradicating staphylococcal bacteria.

Mycobacterium tuberculosis: These bacterium are sensitive to NO and RNS, but in this case, NO2 is the toxic species. A phagosome microenvironment consisting of ROS combined with acidic nitrite generates NO2/N2O3/NO, which is essential for pathogen eradication by the alveolar macrophage. Overall, NO has a dual function; it participates directly in killing an organism, and/or it disarms a pathway used by that organism to elude other immune responses.

Parasites

Many human parasites have demonstrated the initiation of the immune response via the induction of iNOS, that then leads to expulsion of the parasite. The parasites include Plasmodia(malaria), Leishmania(leishmaniasis), and Toxoplasma(toxoplasmosis). Severe cases of malaria have been related with increased production of NO. High levels of NO production are however protective in these cases as NO was shown to kill the parasites (Rockett et al., 1991; Gyan et al., 1994). Leishmania is an intracellualr parasite that resides in the mamalian macrophages. NO upregulation via iNOS induction is the primary pathway involved in containing its infestation. A critical aspect of NO metabolism is that NOHA inhibits AG activity, thereby limiting the growth of parasites and bacteria including Leishmania, Trypanosoma, Schistosoma, Helicobacter, Mycobacterium, and Salmonella, and is distinct from the effects of RNS. Toxoplasma gondii is also an intracellular parasite that elicits NO mediated response. INOS knockout mice have shown more severe inflammatory lesions in the CNS that their wild type counterparts, in response to toxoplasma exposure. This indicates the CNS preventative role of iNOS in toxoplasmosis (Silva et al., 2009).

Virus

Viral replication can be checked by increased production of NO by induction of iNOS (HIV-1, coxsackievirus, influenza A and B, rhino virus, CMV, vaccinia virus, ectromelia virus, human herpesvirus-1, and human parainfluenza virus type 3) (Xu et al., 2006). NO can reduce viral load, reduce latency and reduce viral replication. One of the main mechanisms as to how NO participates in viral eradication involves the nitrosation of critical cysteines within key proteins required for viral infection, transcription, and maturation stages. For example, viral proteases or even the host caspases that contain cysteines in their active site are involved in the maturation of the virus. The nitrosative stress environment produced by iNOS may serve to protect against some viruses by inhibiting viral infectivity, replication, and maturation.

An Investigation of the Potential of circulating Endothelial Progenitor Cells (cEPCs) as a Therapeutic Target for Pharmacological Therapy Design for Cardiovascular Risk Reduction: A New Multimarker Biomarker Discovery

A plethora of new products are emerging as potential therapeutic agents. This calls for detailed studies of their unique pharmacologic characteristics and mechanisms of action in humans. This review written by Caron WP et al (Zamboni’s group) provides a major overview of the factors that affect the pharmacokinetics (PK) and pharmacodynamics (PD) of nanoparticle carries in preclinical models and patients (1). I will use this article as the main source as it was so nicely written yet many other references are added within.

The disposition of carrier-mediated agents (CMAs) is dependent on the carrier and not on the parent drug, until the drug is released from the carrier into the system and includes encapsulated (the drug within or bound to the carrier), released (the active drug that gets released from the carrier), and sum total (encapsulated drug plus released drug).

After the drug has been released from its carrier, it is pharmacologically active and subjected to the same routes of metabolism and clearance (CL) as the non-carrier form of the drug (1,2).

In theory, the PK disposition of the drug after it is released from the carrier should be the same as after administration of the small-molecule or standard formulations. Therefore, the pharmacology and PK of CMAs are complex and call for comprehensive analytical studies to assess the disposition of encapsulated and released forms of the drug in plasma and tumor.

Interindividual variability in drug exposure, represented by area under the plasma concentration– time curve (AUC) of the encapsulated drug and several factor can potentially affect it:

Host-associated characteristics such as gender and age as well as the host mononuclear phagocyte system (MPS), which is a collective term for the immune cells.

Figure 1 here (=figure 3 in the original paper. ref 1) : Nanoparticle clearance and biocompatibility are dependent on various factors including physical characteristics of the carrier as well as physiologic parameters such as the mononuclear phagocyte system (MPS) (reticuloendothelial system (RES)) recognition and enhanced permeability and retention (EPR) effect. There are qualitative relationships between the independent variables, namely, particle size, particle zeta-potential (surface charge), and solubility, and the dependent variable, namely, biocompatibility. Biocompatibility, or extent of exposure (area under the plasma concentration–time curve), includes the route of uptake and clearance (shown in green as the EPR effect and renal and biliary clearance), cytotoxicity (shown in red, can represent either efficacy or toxicities/ adverse events in anticancer treatment), and MPS/RES recognition (shown in blue).

The effect on the immune cells is divided into two categories: (i) responses to nanoparticles that are specifically modified to stimulate the immune system (e.g., vaccine carriers) and (ii) undesirable interactions and/or side-effects.

Immune cells that participate in nanoparticle uptake are circulating monocytes, platelets, leukocytes, and dendritic cells in the bloodstream (3,4). In addition, nanoparticles can be taken up in tissues by phagocytes, e.g., by Kupffer cells in the liver, by dendritic cells in the lymph nodes, by B cells in the spleen, and by macrophages

Uptake mechanisms may occur through different pathways and can often be facilitated by the adsorption of opsonins to the nanoparticle surface

Physical characteristics:

Particle size: In one study of liposomes, particles that had a hydrodynamic diameter between 100 and 200 nm had a fourfold higher rate of uptake in tumors than particles <50 nm or >300 nm.

Surface modification: Conjugated PEG polymer onto the surface- is known to minimize opsonization and thus subsequent decreased rate of MPS uptake overall plasma exposures of drugs contained within PEGylated liposomes were six fold higher than those contained within non-PEGylated liposomes

Surface charge: Uncharged liposomes have lower CLs than either positively or negatively charged liposomes (probably due to reduced opsonization by MPS. rate of CL from blood was significantly higher for negatively charged particles than for uncharged particles

It can be summarized as for their rate of clearance from highest (left) to lowest (right) as:

positive>negative> neutral

Note: PEGylation can alter the alter this rate significantly for example,

Levchenko et al. showed that the negative charge on liposomes can be shielded with this physical alteration, leading to a significantly reduced rate of liver uptake and consequent prolongation of their presence in circulating blood (5).

Host characteristics

Age: In some cases, age-related effects on the PK of some PEGylated liposomal agents have been reported, where in younger male patients (<60) there was a higher rate of clearance of two different agents (Doxil and CDK602) compared to older patients (>60). In other words, in older age, the CL rate was lower and therefore higher AUC/dose. No relation to age was observed for female patients, in the same study.

Alterations in the PK and PD of CMAs may involve accerelated decline in immune system functioning, specifically the association between aging and the functioning of monocytes (6). In theory, there is a loss of MPS activity or function in elderly patients, and this decreases the CL of CMAs by the MPS, leading to increased drug exposures and toxicity in elderly patients. In terms of efficacy, greater age was inversely proportional to progression-free survival; however, no correlation was found between age and overall survival.

Gender: In similar study to the one presented above, female patients had overall lower CL of DOXIL, IHL-305 and CDK602 compared to male patients of the same age.

The basis for the gender-related differences in the PK and PD of CMAs is unclear. It has been hypothesized that some of the differences may be attributed to the effects of sex hormones such as testosterone and estrogen on immune cell function.

Delivery of CMAs Into Tumor

Major advances in the understanding of tumor biology have led to the discovery of targeted agents that can deliver drugs to the desired site while minimizing exposure in normal tissues, thereby minimizing the associated adverse effects. Whereas conventional drugs encounter numerous obstacles en route to their target, CMAs can take advantage of a tumor’s leaky vasculature to extravasate into tissue, via the enhanced permeability and retention effect (EPR).

Note: The extend of the EPR effect is highly debated since although passive targeting through the EPR effect has been a key concept in delivering CMAs to tumors, it does not ensure uniform delivery to all regions of tumor. Furthermore, not all tumors exhibit an EPR effect, and the permeability of vessels may not be the same across any single tumor.

Active targeting may overcome these limitations. The CMAs can be enabled to bind to specific cells in a tumor by using surface attached ligands that are capable of recognizing and binding to cells of interest.

Antibody-mediated targeting has been the method of choice, other targeting strategies using nucleic acids, carbohydrates, peptides, aptamers, vitamins, and other agents are also being evaluated.

Other major points that can affect the PK disposition

The linearity and nonlinearity of the CLs of a drug (might be associated with the dose like with S-CKD602)(7).

Drug-drug interaction (single agent vs combination)

Body composition (Body surface area, body weight)

There are a multitude of properties of CMAs that differ from those of the active small-molecule drugs they contain. These differences lead to significant variability in the PK and PD of carrier- mediated drugs. It has been shown that physical properties, the MPS, the presence of tumors in the liver, EPRs, drug–drug interactions, age, and gender all contribute in varying degrees to the PK disposition and PD end points of CMAs in patients.

Areas of research that can aid in an understanding of how these agents should be used and how we may predict their actions in patients include pharmacogenomics, cellular function (probing the MPS), more sensitive and accurate analytical PK methods, and identification of the optimal preclinical (animal and in vitro) models.

This report is extracted from the article above with editing and shortening as much as possible for the reader, and updated from LCGCNA Aug 12, 2012; 8www.chromatographyonline.com

Part I

Abstract

This review will focus on four state-of-the-art proteomic technologies, namely 2D difference gel electrophoresis, MALDI imaging mass spectrometry, electron transfer dissociation mass spectrometry and reverse-phase protein array. The major advancements these techniques have brought about biomarker discovery will be presented in this review. The wide dynamic range of protein abundance, standardization of protocols and validation of cancer biomarkers, and a 5-year view of potential solutions to such problems is discussed.

Introduction

A common method used for isolating and identifying cancer biomarkers involves the use of serum or tissue protein identification. Unfortunately, currently used tumor markers have low sensitivities and specificities.[2] Therefore, the development of novel tumor markers might be helpful in improving cancer diagnosis, prognosis and treatment.

The rapid development of proteomic technologies during the past 10 years has brought about a massive increase in the discovery of novel cancer biomarkers. Such biomarkers may have broad applications, such as for the detection of the presence of a disease, monitoring of disease clearance and/or progression, monitoring of treatment response and demonstration of drug targeting of a particular pathway and/or target. In general, proteomic approaches begin with the collection of biological specimens representing two different physiological conditions, cancer patients and reference subjects. Proteins or peptides are extracted and separated, and the protein or peptide profiles are compared against each other in order to detect differentially expressed proteins. Commonly, quantitative proteomics is mainly performed by protein separation using either 2DE- or liquid chromatography (LC)-based methods coupled with protein identification using mass spectrometry (MS). Limitations include inability to obtain protein profiles directly from tissue sections for correlation with tissue morphology, limited ability to analyze post-translational modifications (PTMs) and low capacity for high-throughput validation of identified markers. Progress in proteomic technologies has led to the development of 2D DIGE, MALDI imaging MS (IMS), electron transfer dissociation (ETD) MS, and reverse-phase protein array (RPA).

The 2DE method has been one of the mainstream technologies used for proteomic investigations.[3,4] In this method, proteins are separated in the first dimension according to charge by isoelectric focusing, followed by separation in the second dimension according to molecular weight, using polyacrylamide gel electrophoresis. The gels are then stained to visualize separated protein spots,[5] separating up to 1000 protein spots in a single experiment and protein spots are then excised and identified using mass spectrometry (MS).[6,7]

We previously used a 2DE approach to compare the proteomic profiles to identify differentially expressed proteins that may be involved in the development of nasopharyngeal cancer, [8] as well as proteins that were responsive to treatment with the chemotherapeutic agent 5-fluorouracil (5FU) in the colorectal cancer SW480 cell line. Briefly, cell lysates from SW480 cells that were either treated with 5FU or were controls were separated using 2DE. After staining and analysis of the gels, differentially expressed protein spots were excised and identified using MS. The upregulation of heat-shock protein (Hsp)-27 and peroxiredoxin 6 and the downregulation of Hsp-70 were successfully validated by immunohistochemical (IHC) staining of SW480 cells.[9]

The 2D DIGE method improved the 2DE technique. Figure 1 shows how two different protein samples (e.g., control and disease) and, optionally, one reference sample (e.g., control and disease pooled together) are labeled with one of three spectrally different fluorophores: cyanine (Cy)2, 3 or 5. They have the same charge, similar molecular weight and distinct fluorescent properties, allowing their discrimination during fluorometric scanning.[10-12] The minimal dye causes minimal change in the electrophoretic mobility pattern of the protein, whereas the saturation dye labels all available cysteine residues but causes a shift in electrophoretic mobility labeled proteins.[13] The same pooled reference sample used for all gels within an experiment is an internal reference for normalization and spot matching.[12] The gel is scanned at three different wavelengths yielding images for each of the different samples, and variation between gels is minimized and difficulties are reduced in correctly matching of protein spots across different gels.[10,11] Significant advantages of the DIGE technology includes a dynamic range of over four orders of magnitude and full compatibility with MS. However, careful validations of identified markers using alternative techniques are still needed.

In a study that compared three commonly used DIGE analysis software packages, Kang et al. concluded that although the three softwares performed satisfactorily with minimal user intervention, significant improvements in the accuracy of analysis could be achieved .[14] Moreover, it was suggested that results concerning the magnitude of differential expression between protein spots after statistical analysis by such softwares must be examined with care.[14]

The choice of appropriate statistical methods for the analysis of DIGE data has to be considered. Statistical methodological error can be addressed by the use of statistical methods that apply a false-discovery rate (FDR) for the determination of significance. In this method, q-values are calculated for all protein spots. The q-value of each spot corresponds to the expected proportion of false-positives incurred by a change in expression level of that protein spot found to be significant.

Despite the ease of use and enabling the researcher to select an appropriate FDR according to study requirements, this approach was found to be only applicable to DIGE experiments using a two-dye labeling scheme, as a three-dye labeling approach violated the assumption of data independence required for statistical analysis.[16] Other statistical tests that have been applied for the analysis of DIGE results include significance analysis of microarrays,[7] principal components analysis[17,18] and partial least squares discriminant analysis.[18,19] Detailed discussions of the different statistical approaches applicable to proteomic research are beyond the scope of this review and readers may refer to[18,20] for further reading.

Using 2D DIGE, Yu et al. successfully identified biomarkers that were associated with pancreatic cancer.[21] In the study, 24 upregulated and 17 downregulated proteins were identified by MS. Among those proteins, upregulation of apolipoprotein E, α-1-antichymotrypsin and inter-α-trypsin inhibitor were confirmed by western blot analysis. Furthermore, the association of those three proteins with pancreatic cancer was successfully validated in another series of 20 serum samples from pancreatic cancer patients. Using a similar approach, Huang et al. identified and confirmed the upregulation of transferrin in the sera of patients with breast cancer.[22] When Sun et al. compared the proteomic profiles between malignant and adjacent benign tissue samples from patients with hepatocellular carcinoma, they proved 2D DIGE is not limited to serum or plasma samples.[23] In their study, overexpression of Hsp70/Hsp90-organizing protein and heterogenous nuclear ribonucleoproteins C1 and C2 were identified by 2D DIGE coupled with MS analysis, and the findings were successfully validated by both western blotting and IHC staining. Next, Kondo et al. applied 2D DIGE to laser-microdissected cells from fresh patient tissues.[13] Using this protocol, a 1-mm area of an 8-12-µm-thick tissue section was shown to be sufficient. These examples demonstrate the high sensitivity and broad applicability of 2D DIGE for proteomic investigations using various types of patient samples and provide evidence that 2D DIGE is a powerful technique for biomarker discovery.

MALDI Imaging Mass Spectrometry

A deeper understanding of the complex biochemical processes occurring within tumor cells and tissues requires a knowledge of the spatial and temporal expression of individual proteins. Currently, such information is mainly obtained by IHC staining for specific proteins in patient tissues.[8,24,25] Nevertheless, IHC has limited use in high-throughput proteomic biomarker discovery because only a few proteins can be immunostained simultaneously. MALDI IMS allows researchers to analyze proteomic expression profiles directly from patient tissue sections.[26-28] The protocol begins with mounting a tissue section onto a sample plate (Figure 2). MALDI matrix is then applied onto the tissue sample, which is analyzed by MALDI MS in order to obtain mass spectra from predefined locations across the entire patient tissue section. The mass spectrum from each location is a complete proteomic profile for that particular area. All acquired mass spectra from the entire tissue are then compiled to create a 2D map for that tissue sample. This map could then be compared with those from other tissue samples to identify changes in protein or peptide expression or comparisons of the maps from different areas within the same tissue section could be performed. This technology importantly allows the high-throughput discovery of novel protein markers. In addition, correlations between protein expression and tissue histology can also be studied easily.

Most studies using MALDI IMS have been performed on frozen tissue sections ranging from 5 to 20 µm in thickness.[26,27,29] After sectioning, a MALDI matrix is applied either by automated spraying or spotting. The matrix of choice is usually α-cyano-4-hydroxy-cinnamic acid for peptides and sinapinic acid (3,5-dimethoxy-4-hydroxycinnamic acid) for proteins.

Spotting allows the precise application of matrix to areas of interest and minimizes the diffusion of analyte material across the sample, although the imaging resolution achieved by spotting is lower (~150 µm). A laser beam is then fired towards the area of interest on the tissue section to generate protein ions for analysis by a mass analyzer.[29] Among the different mass analyzers, TOF analyzers are the most commonly used owing to their high sensitivity, broad mass range and suitability for detection of ions generated by MALDI. Use of other mass analyzers such as TOF-TOF, quadrupole TOF (QTOF), ion traps (ITs) and Fourier transform-ion cyclotron resonance (FT-ICR) have also been reported in other studies.[30-33]

After obtaining the mass spectra, statistical analysis needs to be performed to identify statistically significant features that could have potential use as biomarkers. But before such analyses can be applied, there has to be background-noise subtraction, spectral normalization and spectral alignment.[34,35,34] Statistical methods used to identify significant differences in peak intensity are symbolic discriminant analysis and principal component analysis. Symbolic discriminant analysis determines discriminatory features and builds functions based on such features for distinguishing samples according to their classification.[36,37] Using this approach, Lemaire et al. found a putative proteomic biomarker from ovarian cancer tissues by MALDI IMS that was later identified to be the Reg-α protein, a member of the proteasome activator 11S.[37] This result was later successfully validated by western blot (protein expression found in 88.8% carcinoma cases vs 18.7% benign disease) and IHC (protein expression found in 63.6% carcinoma tissues vs 16.6% benign tissues).[37] On the other hand, principal component analysis reduces data complexity by transforming data based on peak intensities to information based on data variance, termed ‘principal components’, resulting in a list of significant peaks (principal components) ordered by decreasing variance.[35,38,39] Neither symbolic discriminant analysis or principal component analysis is capable of performing unsupervised classification. This aim requires the use of other methods such as hierarchical clustering.[39,40] In this method identified peaks are clustered as nodes in a pair-wise manner according to similarity until a dendogram is obtained, providing information as to the degree of association of all peak masses in a hierarchical fashion. Peaks that are capable of differentiating between different histological/pathological features could then be chosen for further validation of their value as tumor markers.[39]

In MALDI IMS, protein identification cannot be performed with confidence solely on the molecular weight. However, Groseclose et al. have developed a method using in situ digestion of proteins directly on tissue section.[41] They first used MALDI IMS to obtain a map of the protein and peptide spectra, then spotted a consecutive section of the same tissue sample with trypsin for protein digestion, and then spotted matrix solution onto the digested spots and the resulting peptides are identified directly from the tissue by MS/MS. This modification increases the confidence in protein identification. The time required for MALDI IMS analysis per tissue section is as follows: tissue sectioning, mounting and matrix application: 4-8 h; MALDI image acquisition: 1-2 days; spectral analysis: 1-2 h.[33,39]

Recently, in situ enzymatic digestion has been successfully applied for improving the retrieval of peptides directly from formalin-fixed, paraffin-embedded FFPE tissue samples.[27] Such development has greatly facilitated the application of MALDI IMS in FFPE tissues.[26,42] In fact, Stauber et al. identified the downregulation of ubiquitin, transelongation factor 1, hexokinase and neurofilament M from FFPE brain tissues of rat models of Parkinson disease using this modified technique.[42] The success of performing proteomic profiling using MALDI IMS directly on FFPE tissues opens up great possibility for using archival patient materials in high-throughput biomarker discovery. Novel cancer biomarkers identified using MALDI IMS still require validation by other techniques such as IHC.

Electron Transfer Dissociation MS

Post-translational modifications play important roles in the structure and function of proteins such as protein folding, protein localization, regulation of protein activity and mediation of protein-protein interaction. Two common forms of PTM that have been implicated in cancer development are phosphorylation and glycosylation. Previously, phosphoproteomic studies have led to the identification of novel tyrosine kinase substrates in breast cancer,[43] discovery of novel therapeutic targets for brain cancer[44] and increased understanding of signaling pathways involved in lung cancer formation.[45,46] Conversely, the identification of abnormally glycosylated proteins, such as mucins, has provided novel biomarkers and therapeutic targets for ovarian cancer.[47]

The study of PTM begins with digesting the target protein using enzymes such as trypsin, introducing the fragments into MS for determination of the sites and types of modification and, at the same time, identification of the protein. The analysis is conventionally carried out using collision-induced dissociation (CID) MS, where peptides are collided with a neutral gas for cleavage of peptide bonds to produce b- and y-type ions (Figure 3). A complete series of peptides differing in length by one amino acid is produced, leading to identification of the protein by peptide-sequence determination. However, for phosphopeptides, the presence of phosphate groups would compete with the peptide backbone as the preferred cleavage site. The end result is a reduced set of peptide fragments, which hinders protein identification, and the exact location of the phosphate group on the peptide cannot be determined accurately when there are more than one possible phosphorylation sites.[48,49]

Electron transfer dissociation is a recently developed dissociation technique for the analysis of peptides by MS, utilizing radiofrequency quadrupole ion traps such as 2D linear IT, spherical IT and Orbitrap™ (Thermo Fisher Scientific Inc., MA, USA) mass analyzers.[48,49] In this technology, peptides are fragmented by transfer of electrons from anions to induce cleavage of Cα-N bonds along the peptide backbone, hence producing c- and z-type ions (Figure 3). In contrast to CID, ETD preserves the localization of labile PTM and also provides peptide-sequence information.[48] But ETD fails to fragment peptide bonds adjacent to proline, which are readily cleaved by CID.[50] A study that compared the performance of CID with that of ETD found that only 12% of the identified peptides were commonly detected between the two techniques. A study reported that CID successfully identified more peptides with charge states of +2 and below, whereas ETD was found to be better at identifying peptide ions with charge states of greater than +2.[51] Therefore, it is suggested that CID and ETD should be used together to complement each other.[52] Han et al. successfully differentiated the isobaric amino acids isoleucine and leucine from one another by performing CID on the resulting z-ions after ETD. The presence of isoleucine residue was then confirmed by the detection of a specific 29-Da loss from the peptide.[53] A clear advantage of using ETD for the analysis of phosphopeptides is a near complete series of c- and z-ions without loss of phosphoric acid,[48] greatly facilitating the determination of the phosphorylation sites and the identification of phosphopeptides. Recently, an analysis of yeast phosphoproteome using ETD successfully identified 1252 phosphorylation sites on 629 proteins, whose expression levels ranged from less than 50 to 1,200,000 copies per cell.[54] In another study using ETD, a total of 1435 phosphorylation sites were identified from human embryonic kidney 293T cells, of which 1141 (80%) were previously unidentified. Finally, a study by Molina et al. successfully identified 80% of the known phosphorylation sites in more than 1000 yeast phosphopeptides in one single study using a combination of ETD and CID.[55] In addition, ETD could be applied to investigate other forms of PTM, such as N-linked glycosylations.[56,57]N-linked glycans contain a common core with branched structures. These can be processed by stepwise addition or removal of monosaccharide residues linked by glycosidic bonds, producing highly varied forms of N-linked glycan structures.[58-60] A weakness of analyzing glycopeptides using CID is that cleavage of glycosidic bonds occurs with little peptide backbone fragmentation, so that only the glycan structure is available.[61] Hogan et al. used CID and ETD together to overcome this problem determining the glycan structure and glycosylation site.[61] ICID was initially used for cleavage of glycosidic bonds that allowed the entire glycan structure to be inferred from the CID spectrum alone. ETD was later performed to dissociate the same peptide that resulted in a contiguous series of fragment ions with no loss of glycan molecules, allowing the identification of both the site of glycosylation and the identity of the glycoprotein.[61] Readers are strongly encouraged to refer to[49] and.[62] In a comprehensive comparison of CID versus ETD for the identification of peptides without PTMs, CID was found to identify 50% more peptides than ETD (3518 by CID vs 2235 by ETD), but ETD provided somewhat better sequence coverage (67% for CID vs 82% for ETD). It turns out that ETD produced more uniformly fragmented ions with intensities that were five- to ten-times lower than those produced by CID.[55] Finally, the best sequence coverage of up to 92% was achieved when consecutive CID and ETD were performed.[55]

This increase in sequence coverage using the combined approach is needed for studies requiring de novo peptide identifications. As such, this strategy is particularly suited for studies involved in the discovery, identification and characterization of novel peptides or proteins and their PTMs for biomarker use. A prerequisite of this technique is that the biological samples under investigation must undergo some form of fractionation before they are amenable to analysis by ETD or CID. This is achieved by the use of LC techniques, such as reverse-phase, strong cation exchange or strong anion exchange chromatography, and serves to reduce the complexity and wide dynamic range of protein-expression levels commonly found in biological specimens. Given the important roles of PTM in the function and activity of proteins, this technology paves the way for exploring the intricate cellular activities within a cancer cell.

Advanced Proteomic Technologies for Cancer Biomarker Discovery

Part II

Reverse-phase Protein Array

One of the goals of proteomics is to identify protein changes associated with the development of diseases such as cancer. Even with the rapid development of proteomic technologies during the past few years, analysis of patient samples is still a challenge. Difficulties arise from the fact that[63,64]:

Proteomic patterns differ among cell types;

Protein expression changes occur over time;

Proteins have a broad dynamic range of expression levels spanning several orders of magnitude;

Proteins can be present in multiple forms, such as polymorphisms and splice variants;

Many proteomic technologies cannot be used to study protein-protein interactions.

The principle of RPA is simple and involves the spotting of patient samples in an array format onto a nitrocellulose support (Figure 4). Hundreds of patient specimens can be spotted onto an array, allowing a comparison of a large number of samples at once.[65] Each array is incubated with one particular antibody, and signal intensity proportional to the amount of analyte in the sample spot is generated.[66] Signal detection is commonly performed by fluorescence, chemiluminescence or colorimetric methods. The results are quantified by scanning and analyzed by softwares such as P-SCAN and ProteinScan, which can be downloaded from[84] for free.[67,68]

Any samples spotted as a dilution allows quantifying in the linear range of detection;

Quantitative measurement of any protein is possible compared to reference standards of known amounts on the same array.

It has been shown that RPA is extremely sensitive as it is capable of detecting up to zeptomole (1 x 10-21 mole) levels of target proteins with less than 10% variance. The analysis of few cell signaling events is known.[65,70,71] The assay sensitivity depends on antibody affinity, which depends upon antigen-antibody pairs.[68] Of course, only known proteins with available antibodies can be identified. Therefore, this method is more suitable for biomarker screening or validation than discovery of novel proteins. To assist researchers in selecting suitable antibodies, two open antibody databases show their western blot results using cell lysates.[72,73,85,86]

One application of RPA is to investigate the signaling pathways in human cancers. Zha et al. compared the survival signaling events between Bcl 2-positive and -negative lymphomas and found that survival signals, independent of Bcl 2 expression, were detected in follicular lymphoma and confirmed by validation with IHC.[71] In another study, patient-specific signaling pathways have been identified in breast cancers using RPA. Bayesian clustering of a set of 54 subjects successfully separated normal subjects from cancer patients based on an epithelial signaling signature. Principal component analysis was capable of distinguishing normal from cancer patient samples by using a signature composed of a panel of kinase substrates.[69] Differences in cell signaling between patient-matched primary and metastatic lesions have also been found using RPA. In the study, six patient-matched primary ovarian tumors probed with antibodies against signaling proteins, and the signaling profiles differed significantly between primary and metastatic tumors and upregulation of phosphor c-kit was capable of distinguishing five of the six metastatic tumors from the primary lesions.[70] These findings suggest that treatment strategies may need to target signaling events among disseminated tumor cells.

Reverse-phase protein array has also been used to validate mathematical models of cellular pathways. The p53-Mdm2 feedback loop is one of the most well-studied cellular-feedback mechanisms.[74] Normally, p53 activates transcription and expression of Mdm2, which, in turn, suppresses p53 activity. This negative-feedback loop ensures the low-level expression of p53 under normal conditions. Mathematical models have previously been used to investigate this negative-feedback loop.[67] Ramalingam et al. has shown, by using RPA, that part of the mechanism of the p53-Mdm2 feedback loop can be explained by current mathematical models.[75]

Another important application of RPA is for the identification of cancer specific antigens. Using this method serum from 14 lung cancer patients, colon cancer patients and normal subjects were incubated and eight fractions of the cell lysate were recognized by the sera from four patients, while none of the sera from normal individuals was positive.[76] This study demonstrates the diagnostic potential of identifying cancer antigens that induce immune response in cancer patients by using RPA.

Expert Commentary and Five-year View

The development of 2D DIGE in the past few years has provided researchers with a more accurate method for relative quantification of proteins substantially reducing the number of replicates required for 2D gels and increased its applicability for high-throughput biomarker discovery. MALDI MS has immensely facilitated the direct discovery of biomarkers from patient tissue. Even though archival patient tissue samples are a potential source of materials for tumor marker research, high-throughput techniques for biomarker discovery using such samples has been problematic. With the development of MALDI IMS, investigators can now perform studies that aim to discover novel biomarkers directly from tissue sections and are able to correlate their expression with the histopathological changes of tumors. Previously, investigation into the sites of protein PTM has been difficult since MS-dissociation techniques, such as CID, would lead to preferential loss of PTM, but the use of ETD as a complementary peptide ion-dissociation method has allowed researchers to investigate the precise location and structure of the PTM, and to identify peptide sequence with higher confidence.

The rapid technological improvements in proteomic technologies will identify potential biomarkers for clinical use. Independent validation studies using clinical specimens must be performed before such markers can be applied clinically,. In this regard, RPA has added a potential for high-throughput screening or validation of newly found markers. Using this technique, it will be possible for researchers to quantitatively measure and validate novel markers on hundreds of patient samples simultaneously.

A big problem for proteomic researchers iincludes the abundance of proteins in biological samples. This could be partially solved by depletion of abundant proteins or by fractionation of protein samples according to characteristics. It is envisaged that, in the future, proteomic technologies will be developed to a stage that is capable of analyzing complex protein mixtures without preparatory fractionation. Such progress has recently been achieved in LC-MS, where the use of a high-field, asymmetric waveform, ion-mobility spectrometry device as an interface to an IT MS resulted in a more than fivefold increase in dynamic range without increasing the length of the LC-MS analysis.[77]

Another area that needs improvement is the standardization of protocols for patient-sample collection because results were found to be inconsistent among various studies using MS.[78] It is also considered that part of the reason for this inconsistency is due to the differences in sample-collection or sample-handling procedures.[78,79] The Human Proteome Organization previously published its findings on pre-analytical factors that affect plasma proteomic patterns and provides suggestions for sample handling.[80,81] In addition to the pre-analytical stages, it is imperative to stress that consistent and strict adherence to predefined procedures or standards, from sample collection, sample processing, experimentation, data analysis through to result validation, are of utmost importance to minimize variations and achieve consistent and reproducible results.

Any newly identified potential biomarker must also be validated using an independent cohort of patients in order to establish its clinical value, but the translation of results from the laboratory to the clinic has been slow. Consequently, it has been suggested that quantitative MS could be used for the detection of proteins.[82] The increasing availability of MS facilities to researchers worldwide will facilitate the detection, measurement and validation of protein biomarkers using quantitative MS techniques. Even after validation of such results in the laboratory, diagnostic tests will need to be developed for the marker and large-scale clinical trials would also have to be performed to confirm the results. All these efforts require cooperation of personnel from various disciplines, such as scientists, medical professionals, pharmaceutical companies and governments. Finally, it is hoped that, through improved understanding of the protein expression as cancer progresses will lead to the discovery and development of useful cancer biomarkers for patient diagnosis, prognosis, monitoring and treatment.

Key Issues

2DE coupled with mass spectrometry has been the main workhorse for the proteomic discovery of novel biomarkers in the past 10 years, and the development of 2D difference gel electrophoresis has substantially improved the quantification accuracy of 2DE.

MALDI imaging mass spectrometry has allowed the identification of novel proteomic features directly from patient tissue section for correlation with histopathological changes.

Electron transfer dissociation mass spectrometry has opened up the possibility of identifying the structure and localization of the post-translational modification and the peptide/protein.

Reverse-phase protein array is a powerful tool for the high-throughput validation of novel biomarkers across hundreds of patient samples simultaneously.

30 years of LCGC

The key advances in separation science is covered in five areas of the discipline:

sample preparation

gas chromatography(GC) columns

GC instrumentation

liquid cheomatography (LC) columns

LC instrumentation

In the first, there is automated sample preparation in kit form (QuEChERS). A short list of automated sample preparation techniques includes: supercritical fluid extraction (SFE), microwave extraction, automated solvent extraction (ASE), and solid phase extraction (SPE). A panel of experts views the bast basic method of extraction is SPE, and one uses solid phase microextraction with direct immersion and static headspace extraction, along with liquid-liquid extraction.[2] In GC incremental improvements have been made with ionic liquids, multidimentional GC, and fast GC. LC has advanced dramatically with ultra-high pressure LC and superficially porous particles. LC-MS has become standard equipment routinely used in many labs.[1]

Biomarkers have to be detected in a background of 104-106 other components of comparable concentration that also partition with the stationary phase. The partition coefficients of many species are similar, or identical to the biomarker target. The issue is how to select and resolve fewer than 100 biomarkers from a milieu of 1 million components in a complex mixture. The novel idea is to target structure instead of general properties of molecules.[3] How might this work? A single substrate, metabolite, hormone, or toxin is identified in milliseconds by specific protein receptors. The combinatorial chemistry community has shown that synthetic polynucleotides (aptamers) can be found and amplified that have selectivities approaching antibodies.This is a method well know for years as affinity chromatography. A distinct problem has been the natural process of post translational modification (PTMs), which may create isoforms by addition of a single phosphate ester to be found in the proverbial soup.

Nitric oxide is one of the smallest molecules involved in physiological functions in the body. It is a diatom and thus seeks formation of chemical bonds with its targets rather than structure-function configuration of say protein receptors. Nitric oxide can exert its effects principally by two ways:

Direct

Indirect

Direct actions, as the name suggests, result from direct chemical interaction of NO with its targets e.g. with metal complexes, radical species. These actions occur at relatively low NO concentrations (<200 nM)

Indirect actions result from the effects of reactive nitrogen species (RNS) such as NO2 and N2O3. These reactive species are formed by the interaction of NO with superoxide or molecular oxygen. RNS are generally formed at relatively high NO concentrations (>400 nM)

Credits: Nitric Oxide: Biology and Pathobiology By Louis J. Ignarro

Credits: Nitric Oxide: Biology and Pathobiology By Louis J. Ignarro

Although it can be tempting for scientists to believe that RNS will always have deleterious effects and NO will have anabolic effects, this is not entirely true as certain RNS mediated actions mediate important signalling steps e.g. thiol oxidation and nitrosation of proteins mediate cell proliferation and survival, and apoptosis respectively. As depicted in the figure above, NO concentration determines the action it exerts on different proteins. This is highlighted in the following examples from different studies:

Cells subjected to NO concentration between 10-30 nM were associated with cGMP dependent phosphorylation of ERK

Cells subjected to NO concentration between 30-60 nM were associated with Akt phosphorylation

Besides the concentration, duration of NO exposure also determines how proteins respond to NO. Hence proteins can be ‘immediate’ responders or ‘delayed’ responders. The response can be either ‘transient’ (short lived) or ‘sustained’ (prolonged). Different proteins fall into these different categories. These are not rigid categories rather a functional ‘classification’.

Endogenously generated NO concentration ranges from 2 nM as in endothelial cell to >1 μM in a fully activated macrophage. This wide range, along with the unique chemical reactivity of NO offers immense versatility to the physiological effects that it can exert in different cellular milieu in the body.

In addition to the concentration-dependent effects, other factors that determine the local cellular/tissue milieu add to the complexities involved with signal transduction undertaken by NO. These factors are

rate of NO production

diffusion distance

rates of consumption

reactivity of RNS with molecular targets.

These kinetic determinants play vital role in physiological functions and disease states.

Although it is not possible to detail the modes of modulation of biological functions by NO in a short post, but I hope the post gives a taste of the intricacies involved with NO functions and that there are various parameters that determine the exact role of NO in a biological milieu.